An Extreme Learning Machine Stock Price Prediction Algorithm Based on the Optimisation of the Crown Porcupine Optimisation Algorithm with an Adaptive Bandwidth Kernel Function Density Estimation Algorithm

Published: Aug. 15, 2024

This paper aims to explore the potential application of Extreme Learning Machines (ELM) in stock price prediction and optimise ELM model by combining Crown Porcupine Optimisation Algorithm Adaptive Bandwidth Kernel Function Density Estimation Algorithm. Specifically, model's root mean square error (RMSE) on test set is 0.018, which shows its good accuracy. Meanwhile, correlation coefficient R reaches 0.968, proving effectiveness predicting prices. In addition, determination R² training are 0.987 0.954, respectively, not much different, indicating that has generalisation ability prone overfitting. crucial for practical application, as it implies fits existing data well makes accurate predictions future data. terms other evaluation metrics such Mean Absolute Error (MAE), Root Square Percentage (MAPE), performance excellent both sets. Together, these results indicate after optimising introducing crown porcupine optimisation algorithm adaptive bandwidth kernel function density estimation algorithm, can effectively capture changing pattern, thus achieving efficient prediction. summary, this study only demonstrates great but also highlights importance improving through advanced optimisation, provides a new way thinking methodology financial market analysis. strongly supports investors' decision-making lays foundation related research.

Language: Английский

The impact of self-service technologies on customer engagement in Nigerian fuel stations: exploring the roles of corruption mitigation and trust

African Journal of Economic and Management Studies, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 22, 2025

Purpose This study aims to investigate the impact of customer willingness adopt self-service technologies (SST) in Nigerian fuel station context. Specifically, it explores interplay between corruption mitigation at stations, trust and intimacy shaping attitudes towards SST adoption. Design/methodology/approach The research employs a quantitative approach; partial least squares structural equation modelling (PLS-SEM) software was conducted using an online survey sample 233 participants from Nigeria. Findings reveals that use positively correlates with trust, when introduced stations. However, as anticipated by study, stations significantly mediate relationship intimacy. suggests increase customers’ not only enhances chances mitigating but also strengthens trust. Originality/value contributes both academic understanding practical implications. It advances literature on technology adoption exploring unique context study’s originality lies its examination these dynamics within specific cultural operational setting, presenting valuable knowledge for researchers managers seeking improve experiences service quality.

Language: Английский

Enhancing user engagement through adaptive UI/UX Design: A study on personalized mobile app interfaces

Computer Science & IT Research Journal, Journal Year: 2024, Volume and Issue: 5(8), P. 1942 - 1962

Published: Aug. 23, 2024

This paper presents a comprehensive study on developing and evaluating an adaptive UI/UX framework to enhance user engagement in mobile applications through personalized interfaces. The research investigates key factors influencing engagement, including demographics, cognitive abilities, contextual variables. A context-aware adaptation engine was designed adjust interface elements based real-time data dynamically. proposed implemented learning application subjected rigorous usability testing analysis. Results demonstrated significant improvements task completion rates, satisfaction, overall metrics compared non-adaptive contributes valuable insights into the design optimization of interfaces, emphasizing importance personalization creating compelling experiences. Keywords: Adaptive UI/UX, User Engagement, Context-Aware Adaptation, Mobile Application Design.

Language: Английский